Bitcoin ATH and ATL CyclesDraws a vertical line for ATH and ATL cycles of Bitcoin.
Values are selected based on 1064-364 days analysis.
Bitcoin (Mata Wang Kripto)
NEESON Plus Crypto Market Sentiment IndicatorCore Features
1. Multi-Factor Sentiment Scoring System
Comprehensive Algorithm: Combines 6 different market indicators
Weighted Scoring: Each factor contributes with different weights
Real-time Calculation: Updates with every new bar
Smoothing Mechanism: Triple EMA smoothing for stable signals
2. Advanced Technical Indicators Integration
Multi-Timeframe RSI: 1H, 4H, and Daily RSI analysis
Volume Analysis: Volume spikes and decline detection
ATR Volatility: Market volatility assessment
MACD Momentum: Trend momentum confirmation
Bollinger Bands: Price position analysis
3. Proprietary Indicator Calculations
AHR999 Proxy: Enhanced version for crypto markets
Puell Multiple Proxy: Dynamic calculation with RSI adjustment
PI Cycle Top: Multi-moving average cycle analysis
CBBI Enhanced: Crypto Bull Bear Index with momentum
Market Volatility Sentiment: Volatility-based sentiment scoring
Volume Sentiment: Volume-based market sentiment
Signal Generation System
4. Multi-Condition Signal Filters
Strong Buy/Sell Signals: Multiple confirmation requirements
Warning Signals: Early entry/exit indications
Confirmation Bars: User-configurable signal confirmation
Trend Filter: Optional trend alignment requirement
Volume Filter: Volume spike confirmation
Volatility Filter: ATR-based market condition filtering
Momentum Filter: MACD momentum confirmation
5. Advanced Signal Management
Signal State Tracking: Maintains current position state
Duration Tracking: Tracks how long signals have been active
Entry Score Recording: Records sentiment score at entry
Consecutive Signal Counting: Prevents signal flipping
Exit Conditions: Multiple exit criteria for risk management
Visualization Features
6. Professional Chart Display
Dual Score Plotting: Comprehensive and raw sentiment scores
Color-Coded Background: Real-time market sentiment coloring
Threshold Lines: Clear visual reference levels
Area Fills: Colored zones for different sentiment levels
Signal Markers: Visual indicators for buy/sell signals
7. Information Panel
Real-time Data Display: Current scores and signals
Position Tracking: Duration and entry information
Performance Metrics: Floating P/L calculation
Market Status: RSI, Volume, Volatility, MACD status
Configuration Status: Current filter settings
Customization Options
8. User-Configurable Parameters
Threshold Settings: Adjustable buy/sell/exit levels
Filter Toggles: Enable/disable various filters
Indicator Periods: Customizable calculation periods
Color Settings: Fully customizable color scheme
Signal Duration: Minimum signal duration requirements
9. Alert System
Strong Buy/Sell Alerts: Immediate notification for strong signals
Warning Alerts: Early signal notifications
Custom Alert Messages: Clear, descriptive alert texts
Multiple Timeframe Compatibility: Works across all timeframes
Risk Management Features
10. Built-in Protection Mechanisms
Signal Confirmation: Prevents false signals
Exit Triggers: Multiple exit conditions
Position Duration Limits: Automatic exit after prolonged periods
Profit/Loss Tracking: Real-time performance monitoring
Volatility Adjustment: Adapts to market conditions
Technical Specifications
11. Performance Optimization
Efficient Calculation: Optimized for real-time performance
Multi-Timeframe Support: Works on all chart timeframes
Resource Management: Controlled line and label counts
Precision Control: Adjustable decimal precision
12. Compatibility
Cryptocurrency Focus: Specifically designed for crypto markets
Multi-Asset Support: Works with all TradingView symbols
Platform Compatibility: Fully compatible with TradingView platform
Mobile Support: Responsive design for mobile devices
Usage Benefits
Comprehensive Analysis: Single indicator providing multiple insights
Clear Signals: Easy-to-understand buy/sell indications
Customizable: Adaptable to different trading styles
Risk-Aware: Built-in risk management features
Professional Grade: Institutional-level analysis tools
User-Friendly: Intuitive visual interface
Educational: Helps understand market sentiment dynamics
This indicator is designed to provide traders with a comprehensive market sentiment analysis tool specifically optimized for cryptocurrency markets, combining traditional technical analysis with crypto-specific metrics.
Bitcoin 60 Day Cycle Tracker (with Alerts) - Bob Loukas MethodBitcoin 60-Day Cycle Tracker
For just $47.00 USD one-off payment
You can pay directly to this URL & I'll setup ASAP - PayPal.Me insert $47 USD & your tradingview userid in payment comment.
Alternatively, pls Private Message (PM) via TradingView for other methods you may wish to use.
🎯 Premium Features
This is the PREMIUM version with full alert functionality. Thank you for your support!
What's Included
All Free Version Features
✅ Automated cycle detection (green/red arrows)
✅ Real-time dashboard with 8 data points
✅ Smart filtering and customization
✅ Bitcoin-only & 1D timeframe lock
⚡ Premium Alert System
Six Automated TradingView Alerts:
⏰ Time-Based Alerts (Proactive)
Day 50 Alert - "Cycle Midpoint"
Fires exactly 50 days into current cycle
10-day advance warning before typical cycle low
Use to: Prepare entry strategy, set price alerts
Message: "Day 50 reached. Approaching typical cycle low window."
Day 55 Alert - "Late Cycle Phase"
Fires exactly 55 days into current cycle
5-day advance warning - optimal preparation window
Use to: Final entry preparation, monitor for weakness
Message: "Day 55 reached. Watch for potential cycle low formation."
Day 60 Alert - "Expected Cycle Low"
Fires exactly 60 days into current cycle
Prime timing window for cycle low
Use to: Heightened attention, execute entry plan
Message: "Day 60 reached. Expected cycle low window."
Day 65 Alert - "Extended Cycle"
Fires if cycle extends beyond 65 days
Warning that cycle is running long
Use to: Recalibrate expectations, reduce urgency
Message: "Day 65 reached. Cycle extending beyond typical range."
📊 Pivot Detection Alerts (Reactive)
New Cycle Low Detected
Fires when green arrow appears (automated pivot detection)
Confirms new cycle has started (resets counter to Day 1)
Use to: Execute planned entry, adjust positions
Message: "New cycle low detected at . Monitor for reversal."
Cycle High Detected
Fires when red arrow appears (automated pivot detection)
Marks significant peak within current cycle
Use to: Take profits, tighten stops, reduce leverage
Message: "Cycle high detected at . Consider position management."
Alert Configuration Recommendations
Notification Settings:
✅ Push Notifications (for time-sensitive signals)
✅ Email (for documentation and record-keeping)
⚠️ SMS (optional - for critical alerts only to avoid spam)
🔗 Webhook (for trading automation - advanced users)
Alert Frequency:
Set to "Once Per Bar Close" (recommended)
Avoid "Once Per Bar" (creates too many false alerts)
Sound Settings:
Different sounds for time-based vs pivot alerts
Louder/distinct sound for Day 60 and Cycle Low alerts
ALERT USAGE STRATEGIES
Strategy 1: Conservative Accumulation
Setup:
Enable: Day 55, Day 60, Day 65, New Cycle Low
Disable: Day 50, Cycle High
Logic:
You want to accumulate near cycle lows only, with advance warning.
Workflow:
Day 55 alert → Start monitoring, prepare buy orders
Day 60 alert → Increase vigilance, refine entry levels
Day 65 alert → Cycle running long, stay patient
New Cycle Low alert → Execute entry (green arrow confirmed)
Strategy 2: Active Trading
Setup:
Enable: All 6 alerts
Logic:
You want to trade both entries (lows) and exits (highs).
Workflow:
Day 50 alert → Start planning entry
Day 55 alert → Prepare entry strategy
Day 60 alert → Ready to execute
New Cycle Low alert → Enter position
Cycle High alert → Take partial profits, set trailing stop
Day 50 alert (next cycle) → Begin exit preparation
Strategy 3: Risk Management
Setup:
Enable: Day 60, Day 65, New Cycle Low, Cycle High
Logic:
You manually identify cycles but want confirmation and miss protection.
Workflow:
Manual analysis identifies approaching cycle low
Day 60 alert → Confirms your analysis timing
New Cycle Low alert → Validates your entry
Cycle High alert → Reminds you to manage position
Day 65 alert → Warns if you're waiting too long
Strategy 4: Automation Setup
Setup:
Enable: New Cycle Low, Cycle High
Configure: Webhooks to trading bot/platform
Logic:
Fully automated trading based on confirmed pivots.
Webhook Payload Example:
json
{
"action": "{{strategy.order.action}}",
"price": "{{close}}",
"cycle_day": "{{plot_0}}",
"ticker": "{{ticker}}"
}
Integration:
3Commas, Alertatron, TradersPost, or custom bot
New Cycle Low → Open long position
Cycle High → Close position or take profit
Advanced Alert Customization
Combining with Other Indicators
Example: Confluence Filter
Set up this indicator's alerts
Add RSI/volume/MA indicator
Create compound alert: "Cycle Low AND RSI < 30"
Result: Only alerts on oversold cycle lows
Example: Multi-Timeframe
Day 60 alert fires (1D)
Switch to 4H chart for precise entry
Wait for 4H confirmation (hammer candle, volume spike)
Enter on 4H timeframe with 1D cycle context
Review Monthly:
Which alerts were most accurate?
Did you follow your plan?
Were false signals clustered in specific conditions?
Adjust sensitivity settings based on results
IMPORTANT NOTES
Respect the Cycle - Not every cycle low is a buy opportunity
Not every cycle high requires an exit
Context matters: bull vs bear market
Position Sizing - Scale in across days 55-65 (not all at once), largest size on green arrow confirmation
Never risk more than 2-5% per alert
Alert Troubleshooting
## Alert Didn't Fire
Possible Causes:
Indicator not showing on chart (timeframe/symbol wrong)
Alert condition not met (e.g., cycle too short)
TradingView server lag (rare)
Alert accidentally deleted/paused
Solution:
Verify indicator is active on chart
Check alert list (clock icon) for status
Recreate alert if missing
Test with Day 1 alert (fires every new cycle)
## Too Many False Alerts
Possible Causes:
Pivot settings too sensitive
Market in consolidation/chop
Frequency set to "Once Per Bar" (not bar close)
Solution:
Increase Pivot Lookback to 7-8
Increase Min Days Between Lows to 53+
Change frequency to "Once Per Bar Close"
Consider disabling alerts in ranging markets
## Missed Cycle Low
Possible Causes:
Pivot lookback too high (not sensitive enough)
Min Days filter blocked detection
Cycle was unusually short (<45 days)
Solution:
Lower Pivot Lookback to 5
Lower Min Days Between Lows to 45-48
Enable Smart Overlapping feature
Supplement with manual analysis
Update Policy
All updates included with premium access
Access tied to your TradingView account
Alert Limitations:
Alerts are based on historical pivot detection (lagging)
Time-based alerts are forward-looking but not predictive
No alert system guarantees profitable trades
Technical failures may prevent alert delivery
Trading Risks:
Alert or Automated trading amplifies both profits and losses
Webhook errors can cause unintended positions
Always test with small size first
Never trade beyond your risk tolerance
No Warranty or Liability:
Indicator provided "as-is"
No guarantee of uptime or accuracy
Not liable for trading losses whatsoever
Not financial advice or recommendations
By using this premium indicator, you acknowledge these risks and accept full responsibility for your trading decisions.
Contact
For premium support questions, use TradingView private messages or the contact method provided at purchase.
For just $47.00 USD one-off payment
Thank you for supporting this project! 🚀
Bitcoin 60 Day Cycle Tracker Automated [Bob Loukas Method]Bitcoin 60-Day Cycle Tracker
🎯 Quick Start
This is the FREE version with visual cycle tracking. Want automated alerts? See "Premium Version" section below.
Overview
The Bitcoin 60-Day Cycle Tracker automatically identifies Bitcoin's recurring ~60-day price cycle pattern based on methodology pioneered by Bob Loukas, creator of the "Bitcoin's 4-Year Journey" series. While Bitcoin's 4-year halving cycle is well-known, this short-term cycle offers precision timing for entries and exits within the larger trend.
What You Get (Free Version)
✅ Automated Cycle Detection
Green arrows mark cycle lows (typically every 50-65 days)
Red arrows mark cycle highs (peaks within each cycle)
Day count labels show time since last cycle low
✅ Real-Time Dashboard
Current cycle day position
Phase indicator (Early/Mid/Late)
Days until expected cycle low (day 60)
Right/Left translation (bullish/bearish structure)
% gain/loss from cycle low
Last cycle low price reference
Rolling 5-cycle average length
Progress percentage
✅ Smart Configuration
Adjustable pivot sensitivity (default: 6-bar lookback)
Minimum cycle spacing filter (default: 51 days)
Optional overlap detection for compressed cycles
✅ Built-In Safeguards
Works only on Bitcoin pairs (all exchanges)
Locked to Daily (1D) timeframe
Displays warning on wrong chart/timeframe
🔒 Premium Version Features
The premium invite-only version adds 6 automated TradingView alerts:
Time-Based Alerts:
🔔 Day 50 Warning (10 days before expected low)
🔔 Day 55 Warning (5 days before expected low)
🔔 Day 60 Alert (expected cycle low timing)
🔔 Day 65 Alert (extended cycle warning)
Pivot Detection Alerts:
📊 New Cycle Low Detected (when green arrow appears)
📊 Cycle High Detected (when red arrow appears)
All alerts support push notifications, email, SMS, and webhook integration for trading automation.
💎 For premium access with alerts, visit my TradingView profile for details.
Understanding the 60-Day Cycle
The Pattern
Bitcoin consistently forms significant price lows approximately every 60 days, creating a predictable rhythm within the larger 4-year cycle. This pattern appears in both bull and bear markets, though interpretation differs.
Key Metrics:
Typical Length: 50-65 days (average: 60 days)
Cycle Count: ~24 cycles per 4-year halving cycle
Variation: Can compress to 42 days or extend to 70 days in volatile conditions
Cycle Translation
Right-Translated Cycles (Bullish)
Peak occurs after day 30 of the cycle
Indicates strong momentum and buyer strength
Common in uptrends and bull markets
Suggests holding positions longer
Left-Translated Cycles (Bearish)
Peak occurs before day 30 of the cycle
Indicates weakness and seller dominance
Common in downtrends and bear markets
Suggests earlier profit-taking
How to Use This Indicator
Entry Timing
Days 50-60 (Late Phase)
The "buy zone" window
Watch for price weakness and capitulation volume
Prepare limit orders near support levels
Wait for green arrow confirmation before entry
Days 1-10 (Early Phase)
Strongest momentum period after cycle low
Breakout confirmation when price crosses 10-day MA
Highest probability zone for position building
Exit Strategy
Days 30-40 (Mid Phase)
Typical cycle high window in strong trends
Monitor for red arrows (cycle high detection)
Consider partial profit-taking
Trailing stops become appropriate
Days 50+ (Late Phase)
Risk increases as new cycle low approaches
Tighten stops or reduce position size
Watch for failed cycle warnings (price below previous low)
Risk Management
Failed Cycle Signals:
Price breaking below previous cycle low = trend weakness
Multiple short cycles (<45 days) = increased volatility
Extended cycles (>65 days) = potential distribution phase
Confluence Factors:
Combine with Bitcoin's 4-year cycle position
Check volume patterns at cycle lows (capitulation)
Verify with on-chain metrics (UTXO age, realized value)
Consider macro liquidity conditions
Configuration Guide
Default Settings (Optimized for BTC 1D)
Pivot Lookback: 6
Min Days Between Cycle Lows: 51
Max Days for Cycle High: 73
Min Days Before Marking High: 15
High Pivot Lookback: 6
Smart Overlapping: OFF
Tuning for Different Market Conditions
More Sensitive (Catches more cycles)
Reduce Pivot Lookback to 4-5
Lower Min Days Between Lows to 45-48
Enable Smart Overlapping
Best for: Volatile/choppy markets
Less Sensitive (Cleaner signals)
Increase Pivot Lookback to 7-8
Raise Min Days Between Lows to 53-55
Disable Smart Overlapping
Best for: Strong trending markets
Balanced (Recommended)
Keep default settings
Adjust only if consistently missing obvious lows
Document your changes for backtesting
Market Context
Bull Markets
Cycle lows offer accumulation opportunities
Right-translation confirms strong trend
Focus on entries near green arrows
Hold through red arrows in strong uptrends
Bear Markets
Cycle lows may be lower lows (downtrend continues)
Left-translation signals sustained weakness
Use for timing short-term bounce trades
Respect red arrows as exit signals
Sideways Markets
Cycles define range boundaries
Trade range: buy near green arrows, sell near red arrows
Repeated left-translation suggests distribution
Right-translation breakout signals trend resumption
Important Limitations
What This Indicator CANNOT Do
❌ Predict exact price targets
❌ Replace comprehensive market analysis
❌ Guarantee cycle timing precision
❌ Account for black swan events or macro shocks
❌ Work on altcoins or non-crypto assets
Accuracy Expectations
This automated tool approximates manual cycle analysis but cannot match human discretion. Professional analysts like Bob Loukas may consider:
Market narrative and sentiment
Volume profile and liquidity
Macro economic factors
On-chain data confluence
Realistic Expectations:
~70-80% accuracy on cycle low timing (±5 to 10 days)
Variable performance in ranging vs trending markets
Best used as timing framework, not standalone system
Complementary Analysis
Practical Examples
Scenario 1: Bull Market Entry
Current Status:
- Cycle Day: 57
- Phase: Late
- Translation: Right (previous cycle)
- % From Low: -4.2%
Action Plan:
1. Price approaching day 60 window
2. Right-translation suggests continued strength
3. Set alerts for volume spike
4. Prepare buy orders 5-8% below current price
5. Wait for green arrow confirmation
6. Enter on day 1-5 of new cycle
Scenario 2: Bear Market Caution
Current Status:
- Cycle Day: 34
- Phase: Mid
- Translation: Left (current cycle peaked day 26)
- % From Low: +18.7%
Action Plan:
1. Left-translation signals weakness
2. Already well into cycle (day 34)
3. Red arrow may appear soon
4. Set tight trailing stop
5. Consider partial profit-taking
6. Avoid new longs this late in weak cycle
Frequently Asked Questions
Q: Why Bitcoin only?
A: The 60-day cycle is a Bitcoin-specific pattern observed over multiple market cycles. Altcoins have different rhythms tied to BTC correlation.
Q: Does it work on lower timeframes?
A: No. The indicator is designed for and locked to the Daily (1D) timeframe. Lower timeframes create too much noise.
Q: Can I use this for leverage trading?
A: Cycle timing can inform leverage entries, but always use proper risk management. The cycle is probabilistic, not guaranteed.
Q: What if a cycle extends past day 65?
A: Extended cycles indicate consolidation or distribution. Reduce position size and wait for confirmation.
Q: How do I know if a cycle "failed"?
A: If price breaks below the previous cycle low, the cycle structure has failed, suggesting trend weakness.
Q: Should I buy every day 60?
A: No. Day 60 is a timing window, not a buy signal. Wait for technical confirmation (green arrow, volume, support hold) and combine with other confluences to decide on the trade.
Changelog
v1.0: Initial public release
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or trading signals.
Key Risks:
Past cycle patterns do not guarantee future results
Automated detection has inherent limitations
Market conditions can invalidate cycle analysis
Always use proper risk management and position sizing
Never trade based solely on one indicator. Combine cycle analysis with fundamental research, technical analysis, risk management, and your own due diligence.
Trading cryptocurrencies carries substantial risk of loss. Only trade with capital you can afford to lose completely.
Credits
Cycle analysis methodology inspired by Bob Loukas and the cryptocurrency cycle analysis community. Automated detection developed independently using pivot analysis and statistical filtering.
📌 Want automated alerts when various cycle trigger points flash? Visit my profile for premium version access.
【MasterHSC】CCI Mean Derivative Smart Strategy🧾 Strategy Description (English)
CCI Mean Slope Smart Strategy
This strategy is built on the derivative slope behavior of the Commodity Channel Index (CCI) mean line.
It identifies key turning points or trend continuations based on how the smoothed CCI (mean value) changes direction after reaching overbought or oversold zones.
Core Idea:
When the CCI mean reverses slope after exceeding ±100, it signals a potential mean reversion (range-trading opportunity).
When the CCI mean remains above +100 or below −100 with a consistent slope, it indicates a strong trending phase (momentum continuation).
The strategy dynamically adapts between these two behaviors depending on market conditions.
Modes:
🌀 Range Reversal Mode — Focuses on slope reversals after overbought/oversold conditions.
🚀 Trend Following Mode — Captures strong momentum when the CCI mean stays extended.
🧠 Auto Mode — Automatically switches between Range and Trend logic based on CCI mean volatility.
Key Features:
Dual-direction toggle: Enable or disable long/short entries independently.
Adjustable tolerance: Choose fixed or dynamic thresholds for flexibility.
Automatic mode label and visual buy/sell markers on the chart.
Pure CCI-based system — no external filters or indicators required.
Purpose:
This system is designed to reduce false signals in sideways markets while preventing missed opportunities during strong directional trends, offering a clean balance between precision and adaptability.
BTC Open interest (binance, bybit, okx, bitget, htx, deribit)📈 BTC Open Interest Candles (Binance, Bybit, OKX, Bitget, HTX, Deribit)
🌟 Overview
This Pine Script indicator fetches real-time Bitcoin (BTC) perpetual futures open interest (OI) data from major cryptocurrency exchanges (Binance, OKX, Bybit, Bitget, HTX, Deribit), aggregates it, and visualizes it as candlesticks on the chart. Each candlestick represents the combined OI values at the open, high, low, and close of that bar. Candlestick colors change based on whether the current bar’s close OI is higher or lower than the previous bar’s, allowing intuitive tracking of OI fluctuations.
✨ Key Features
Multi-exchange OI aggregation: Combines OI data from selected exchanges to create a unified OI candlestick series.
Candlestick visualization: Converts aggregated OI values into open, high, low, and close values to plot candlestick charts, clearly showing the range and trend of OI over time.
Color-coded OI change:
Close OI higher than previous bar → teal candlestick (OI increase)
Close OI lower than previous bar → red candlestick (OI decrease)
⚙️ Inputs
Show Binance true Include Binance OI in the aggregation.
Show OKX true Include OKX OI in the aggregation.
Show Bybit true Include Bybit OI in the aggregation.
Show Bitget true Include Bitget OI in the aggregation.
Show HTX true Include HTX OI in the aggregation.
Show Deribit true Include Deribit OI in the aggregation.
📊 Calculation Methodology
Requests OI open, high, low, close values for the specified exchange using request.security().
Missing data (na) is treated as 0 to prevent aggregation errors.
Returns OI values as arrays.
➕ Aggregation of individual OI
Variables combinedOiOpen, combinedOiHigh, combinedOiLow, combinedOiClose initialized to 0.
Calls getOI for each enabled exchange and adds returned values to the combined variables.
🎨 Candlestick color determination
oiColorCond checks whether combinedOiClose > combinedOiClose .
True → openInterestColor = color.teal (OI increase)
False → openInterestColor = color.red (OI decrease)
🕯 Candlestick plotting
plotCandles ensures at least one exchange is selected.
plotcandle() is called with na values if no exchanges are selected to avoid drawing candles.
Candle body, wick, and border colors follow openInterestColor.
💡 How to Use
🌐 Integrated market sentiment
Observe overall market OI changes using a unified candlestick chart rather than fragmented exchange data to understand market sentiment and capital flow.
🔍 Compare with price movements
Analyze price charts alongside OI candlesticks to see how OI changes affect (or are affected by) price.
🟢 Price rising + teal OI candlestick (OI increase): Indicates bullish momentum from new long entries or short covering.
🔴 Price falling + red OI candlestick (OI decrease): Suggests bearish momentum from long liquidations or increased short covering.
📈 Price rising + red OI candlestick (OI decrease): Could reflect a short squeeze or profit-taking in long positions.
📉 Price falling + teal OI candlestick (OI increase): May indicate new short positions or forced long liquidations (stop-loss triggers).
⚡ Volatility prediction
Large OI candles or consecutive candles of a certain color can indicate imminent or ongoing significant market moves.
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL
Summary in one paragraph
FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close.
Scope and intent
• Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs
• Timeframes. One minute to daily
• Default demo used in the publication. SPY on 30min
• Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state
• Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes
• Testability. All windows and gains are inputs
• Portable yardstick. Returns use natural log units and range is bar high minus low
• Protected scripts. Not used. Method disclosed plainly here
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion
Components
• Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized
• Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression
• Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves
• Energy score. Z scores of the above form a single energy that controls the state gain
• One bar projection. Current slope extended by one bar for anticipatory checks
Fusion rule
Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push.
Signal rule
• Long suggestion and order when close is below trend and the one bar projection is above the trend
• Short suggestion and flip when close is above trend and the one bar projection is below the trend
• WAIT is implicit when neither condition holds
• In position states end on the opposite condition
What you will see on the chart
• Colored trendline teal for rising red for falling gray for flat
• Optional projection line one bar ahead
• Optional background can be enabled in code
• Alerts on price cross and on slope flips
Inputs with guidance
Setup
• Price source. Close by default
Logic
• Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips
• Vol window. Typical range 30 to 120. Higher calms curvature
• Energy window. Typical range 20 to 80. Higher slows regime changes
• Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop
UI
• Show 1 bar projection. Colors for up down flat
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• Commission percent 0.03
• Slippage 5
• Default order size method percent of equity value 3%
• Pyramiding 0
• Process orders on close off
• Calc on every tick off
• Recalculate after order is filled off
Realism and responsible publication
• No performance claims
• Intrabar reminder. Shapes can move while a bar forms and settle on close
• Strategy uses standard candles only
Honest limitations and failure modes
• Sudden gaps and thin liquidity can still produce fast flips
• Very quiet regimes reduce contrast. Use larger windows and lower max gain
• Session time uses the exchange time of the chart if you enable any windows later
• Past results never guarantee future outcomes
Open source reuse and credits
• None
Digital Credit: Yields, Spreads & Regime
TN Preferreds is a yield-centric dashboard for bitcoin backed preferreds that overlays effective yields. It builds credit/benchmark spread series, a simple regime model (Risk-On / Cautious / Risk-Off), and a compact table that surfaces price, yield, target, upside and diagnostics—so you can quickly judge relative value and risk conditions.
What it does:
Plots effective yields for STRF/STRC/STRK/STRD (+ CNLTN toggle).
Pulls IG (FRED:BAMLC0A0CMEY), HY (FRED:BAMLH0A0HYM2EY) and US10Y as references.
Computes Credit Spreads vs US10Y and Benchmark Spreads (F−IG, C−IG, K−IG−1%, D−HY) with EMAs/SMA for context.
STRC monthly rate input: set 12 monthly percentages; the current month auto-applies to compute the dividend.
Targets & upside: yield-parity targets for each series + % move to target
Leader logic: picks the series with the strongest SMA-based spread improvement and estimates a leader target price.
Risk regime: EMA-based deltas across spreads define Risk-On / Cautious / Risk-Off; optional background + last-bar label.
Table view (bottom-right): price, eff. yield, target, upside, CS, BS, BS-EMA, BS-Diff, leader stats, regime deltas.
Notes:
Designed for overlay on any chart (format = percent, right scale). Works best with a yield based basis like US10Y
• FRED series must be available on your TradingView plan/region.
Educational tool, not investment advice. Always validate assumptions (dividends, conversion terms, required spreads).
Bitcoin ETF Cumulative Net InflowIndicator Description:
This indicator calculates and plots the cumulative net inflow (in billions of USD) for selected Bitcoin ETFs on the main price chart. It uses AUM data from TradingView to estimate daily net flows, adjusted for BTC price changes, and accumulates them over time. The line is overlaid on the price chart (e.g., BTCUSD) with a right scale for better visibility, helping to identify correlations between ETF inflows and Bitcoin price movements.
Key Features:
Supports selection of 10 major Bitcoin ETFs (IBIT, FBTC, ARKB, etc.) via inputs.
Cumulative inflow line (purple, linewidth=2) for trend analysis.
Data sourced from request.financial("AUM", "D") for accuracy.
RSI Crypto Strength (Asset vs BTC)The "RSI Crypto Strength" is an advanced analysis tool built on a fundamental pillar of the cryptocurrency market: for an altcoin to achieve exponential bullish performance, it must invariably be and remain stronger than Bitcoin itself.
The primary objective of this indicator is to quantify and reinforce this thesis. It provides a clear and immediate view of the relative strength of any cryptocurrency in direct comparison with the market leader, Bitcoin. This relative strength can be identified on any timeframe. This also reinforces a scenario where a cryptocurrency that is weaker than Bitcoin is prone to sideways movements and downturns.
Key Features
This indicator combines multiple tools into a single solution:
> Dual RSI Plot: Simultaneously visualizes the RSI of the asset on the chart (dynamic) and the RSI of Bitcoin (blue line).
> Strength Delta (Asset vs. BTC): The heart of the indicator. A panel displays the exact difference (Asset RSI - Bitcoin RSI).
- Green: The asset has more RSI strength than Bitcoin.
- Red: The asset has less RSI strength than Bitcoin.
> Dynamic Coloring and Area Fill: The asset's RSI line and the background area automatically change color to highlight critical zones:
- Green (Overbought): RSI above 70.
- Red (Oversold): RSI below 30.
- Orange (Neutral): RSI between 30 and 70.
> Integrated Moving Average: A Moving Average line (gray) is plotted directly on the asset's RSI, serving as a signal line or to smooth momentum. The type (SMA, EMA, WMA, etc.) and period are fully customizable.
> Multi-Timeframe (MTF) Support: You can configure the indicator to display data from a higher timeframe (e.g., "1H") while analyzing a lower timeframe chart (e.g., "5m").
> Customizable Panel and Labels:
- A Delta Panel that can be enabled/disabled and moved to any of the four corners of the indicator.
- Labels at the end of the lines (Asset, BTC, MA) for easy identification, which can also be enabled/disabled.
> Alert-Ready: The indicator exposes the 4 main data sources for creating alerts.
How to Use
> Thesis Validation (Higher Timeframes): This is the primary use. Before looking for entries, use the indicator on timeframes like the H4, Daily, or Weekly. Confirm that the Asset (orange/green line) is consistently above Bitcoin (blue line) and that the Delta is positive. This is your structural strength validation, confirming the asset has potential for an exponential rally.
> Delta Analysis: The "Delta (Asset - BTC)" panel is your immediate strength metric. A positive and rising value indicates the asset is outperforming Bitcoin. A negative and falling value indicates relative weakness.
> Line Crossovers (Timing): On lower timeframes, watch for crossovers between the Asset line and the Bitcoin line. A cross of the Asset line above the Bitcoin line is a clear sign that the asset's momentum is gaining strength.
> Signal Confluence: Look for high-probability scenarios. For example: The Asset's RSI crosses above the Bitcoin RSI while the Delta also crosses above 0.
> Market Extremes: Use the area fill to quickly identify when the asset reaches extreme overbought (>70) or oversold (<30) levels, regardless of what Bitcoin is doing.
Alerts
This indicator is fully prepared for alert creation. When setting up an alert in TradingView, you can select the following data sources from this indicator:
> RSI Asset: Alerts on the RSI value of the asset on the chart.
> RSI Bitcoin: Alerts on the RSI value of Bitcoin.
> Moving Average: Alerts on the value of the Moving Average.
> RSI Delta: Allows creating alerts based on the difference between the two. (e.g., "Alert if RSI Delta crosses above Value 0").
Settings (Inputs)
The indicator offers full customization:
> RSI Length: The calculation period for both RSIs (default 14).
> Indicator Timeframe: Enables Multi-Timeframe functionality.
> Bitcoin Ticker: Allows changing the Bitcoin reference ticker.
> MA Settings: Choose the MA Type (SMA, EMA, WMA, VWMA, etc.) and its period.
> Panels and Labels: Toggles to enable/disable the Delta Panel and Line Labels, plus a selector for the panel's location.
> Colors: All line and highlight colors are fully customizable in the settings.
DISCLAIMER: This script is an analysis tool and does not provide financial advice. All trades carry risk. Use this tool as part of a broader trading strategy and always practice good risk management.
Crypto Fear and Greed Index📊 Crypto Fear & Greed Index — by @victhoreb
Decode the emotional pulse of the crypto market with this all-in-one Fear & Greed Index! 🧠💰 This custom-built indicator blends 7 powerful market signals into a single sentiment score ranging from 0 (😱 Extreme Fear) to 100 (🚀 Extreme Greed), helping you spot potential tops, bottoms, and trend shifts with clarity.
🔍 What’s under the hood?
Each component reflects a unique psychological or macroeconomic force:
- ⚡ Market Momentum: Measures how far BTC is from its 125-day average — are we overextended or undervalued?
- 📈 Crypto Price Strength: Tracks the dominance of altcoins (OTHERS.D) — rising dominance = growing risk appetite.
- 💵 Digital Dollar Dominance (USDT.D): A proxy for stablecoin demand — more USDT dominance = risk-off behavior.
- 🐦 Twitter Sentiment (LunarCrush): Captures real-time posts on TWITTER about Bitcoin — are the crowds euphoric or panicking?
- 🌪️ Volatility (VIX): Inverted VIX deviation — higher fear in traditional markets often spills into crypto.
- 🛡️ Safe Haven Demand: Compares BTC returns vs. US10Y bonds — are investors fleeing to safety or embracing risk?
- 🧨 Junk Bond Demand (BAMLH0A0HYM2): Inverted high-yield spread — tighter spreads = more greed in credit markets.
🎯 Why use it?
This index gives you a quantified view of market sentiment, helping you:
- Anticipate reversals during emotional extremes
- Confirm trend strength or weakness
- Stay objective when the market gets irrational
🧭 Visual Dashboard
A custom offset sentiment meter shows current positioning with intuitive labels:
- 😱 Extreme Fear
- 😨 Fear
- 😐 Neutral
- 😄 Greed
- 🚀 Extreme Greed
Color gradients and dynamic labels make it easy to interpret at a glance.
Ready to trade with the crowd—or against it? Add this indicator to your chart and let sentiment guide your strategy! 📈🧠
LRHS Strategy - (@BAKARAFX)LRHS Strategy by @Bakarafx
🇫🇷 Indicateur avancé conçu pour identifier les zones de retournement potentielles basées sur les chasses de liquidités et la structure du marché.
Il aide les traders à comprendre où les grands acteurs piègent les participants avant un mouvement significatif, et à repérer les points clés de renversement avec précision.
⚙️ Fonctionnalités principales :
• Détection automatique des chasses de liquidités (hauts/bas précédents).
• Lecture multi-timeframe avec filtrage intelligent selon le timeframe de chasse et de confirmation.
• Signaux visuels clairs indiquant les zones de renversement structurel
• Outil compatible avec Bitcoin et Ethereum
• Optimisé pour le price action
🇺🇸 An advanced indicator designed to identify potential reversal zones based on liquidity hunts and market structure.
It helps traders understand where major players trap participants before a significant move, allowing for more precise detection of key reversal points.
⚙️ Main Features:
• Automatic detection of liquidity grabs (previous highs/lows)
• Multi-timeframe analysis with smart filtering between hunt and confirmation timeframes
• Clear visual signals highlighting structural reversal zones
• Compatible with Bitcoin and Ethereum
• Optimized for price action trading
📍 Développé par : @Bakarafx
⚠️ Disclaimer / Avertissement
This indicator is for educational and informational purposes only.
It does not constitute financial or investment advice.
Trading involves a high level of risk, and the author is not responsible for any financial losses that may occur.
Always do your own analysis and risk management before taking a trade.
Past performance does not guarantee future results.
Hyper SAR Reactor Trend StrategyHyperSAR Reactor Adaptive PSAR Strategy
Summary
Adaptive Parabolic SAR strategy for liquid stocks, ETFs, futures, and crypto across intraday to daily timeframes. It acts only when an adaptive trail flips and confirmation gates agree. Originality comes from a logistic boost of the SAR acceleration using drift versus ATR, plus ATR hysteresis, inertia on the trail, and a bear-only gate for shorts. Add to a clean chart and run on bar close for conservative alerts.
Scope and intent
• Markets: large cap equities and ETFs, index futures, major FX, liquid crypto
• Timeframes: one minute to daily
• Default demo: BTC on 60 minute
• Purpose: faster yet calmer PSAR that resists chop and improves short discipline
• Limits: this is a strategy that places simulated orders on standard candles
Originality and usefulness
• Novel fusion: PSAR AF is boosted by a logistic function of normalized drift, trail is monotone with inertia, entries use ATR buffers and optional cooldown, shorts are allowed only in a bear bias
• Addresses false flips in low volatility and weak downtrends
• All controls are exposed in Inputs for testability
• Yardstick: ATR normalizes drift so settings port across symbols
• Open source. No links. No solicitation
Method overview
Components
• Adaptive AF: base step plus boost factor times logistic strength
• Trail inertia: one sided blend that keeps the SAR monotone
• Flip hysteresis: price must clear SAR by a buffer times ATR
• Volatility gate: ATR over its mean must exceed a ratio
• Bear bias for shorts: price below EMA of length 91 with negative slope window 54
• Cooldown bars optional after any entry
• Visual SAR smoothing is cosmetic and does not drive orders
Fusion rule
Entry requires the internal flip plus all enabled gates. No weighted scores.
Signal rule
• Long when trend flips up and close is above SAR plus buffer times ATR and gates pass
• Short when trend flips down and close is below SAR minus buffer times ATR and gates pass
• Exit uses SAR as stop and optional ATR take profit per side
Inputs with guidance
Reactor Engine
• Start AF 0.02. Lower slows new trends. Higher reacts quicker
• Max AF 1. Typical 0.2 to 1. Caps acceleration
• Base step 0.04. Typical 0.01 to 0.08. Raises speed in trends
• Strength window 18. Typical 10 to 40. Drift estimation window
• ATR length 16. Typical 10 to 30. Volatility unit
• Strength gain 4.5. Typical 2 to 6. Steepness of logistic
• Strength center 0.45. Typical 0.3 to 0.8. Midpoint of logistic
• Boost factor 0.03. Typical 0.01 to 0.08. Adds to step when strength rises
• AF smoothing 0.50. Typical 0.2 to 0.7. Adds inertia to AF growth
• Trail smoothing 0.35. Typical 0.15 to 0.45. Adds inertia to the trail
• Allow Long, Allow Short toggles
Trade Filters
• Flip confirm buffer ATR 0.50. Typical 0.2 to 0.8. Raise to cut flips
• Cooldown bars after entry 0. Typical 0 to 8. Blocks re entry for N bars
• Vol gate length 30 and Vol gate ratio 1. Raise ratio to trade only in active regimes
• Gate shorts by bear regime ON. Bear bias window 54 and Bias MA length 91 tune strictness
Risk
• TP long ATR 1.0. Set to zero to disable
• TP short ATR 0.0. Set to 0.8 to 1.2 for quicker shorts
Usage recipes
Intraday trend focus
Confirm buffer 0.35 to 0.5. Cooldown 2 to 4. Vol gate ratio 1.1. Shorts gated by bear regime.
Intraday mean reversion focus
Confirm buffer 0.6 to 0.8. Cooldown 4 to 6. Lower boost factor. Leave shorts gated.
Swing continuation
Strength window 24 to 34. ATR length 20 to 30. Confirm buffer 0.4 to 0.6. Use daily or four hour charts.
Properties visible in this publication
Initial capital 10000. Base currency USD. Order size Percent of equity 3. Pyramiding 0. Commission 0.05 percent. Slippage 5 ticks. Process orders on close OFF. Bar magnifier OFF. Recalculate after order filled OFF. Calc on every tick OFF. No security calls.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Shapes can move while a bar forms and settle on close. Strategies execute only on standard candles.
Honest limitations and failure modes
High impact events and thin books can void assumptions. Gap heavy symbols may prefer longer ATR. Very quiet regimes can reduce contrast and invite false flips.
Open source reuse and credits
Public domain building blocks used: PSAR concept and ATR. Implementation and fusion are original. No borrowed code from other authors.
Strategy notice
Orders are simulated on standard candles. No lookahead.
Entries and exits
Long: flip up plus ATR buffer and all gates true
Short: flip down plus ATR buffer and gates true with bear bias when enabled
Exit: SAR stop per side, optional ATR take profit, optional cooldown after entry
Tie handling: stop first if both stop and target could fill in one bar
Quantum Flux Universal Strategy Summary in one paragraph
Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version.
Scope and intent
• Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto
• Timeframes. One minute to daily
• Default demo used in the publication. QQQ on one hour
• Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps.
• What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise.
• Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state.
• Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols.
Method overview in plain language
The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction.
Base measures
• Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale.
• Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop.
• Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves.
Components
• Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner.
• Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends.
• Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response.
• Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance.
• Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot.
Fusion rule
• Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent.
• The blend power input scales the driver mix. Zero means fixed spans. One means full driver control.
• Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes.
Signal rule
• Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one.
• Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one.
• When polarity flips from plus to minus, the strategy closes any long and enters a short.
• When flux crosses above the guide, the strategy closes any short.
What you will see on the chart
• White polarity plot around the zero line
• A dotted reference line at zero named Zen
• Green background tint for positive polarity and red background tint for negative polarity
• Strategy long and short markers placed by the TradingView engine at entry and at close conditions
• No table in this version to keep the visual clean and portable
Inputs with guidance
Setup
• Price source. Default ohlc4. Stable for noisy symbols.
• Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive.
• Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price.
Logic
• Guide span. Typical range 4 to 12. A small guide smooths without eating turns.
• Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing.
• Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work.
• Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise.
• Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve.
• Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak.
• Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong.
• Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline.
• Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols.
• Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs.
Filters
• Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends.
• Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping.
• Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version.
Alerts
• This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows.
Strategy has been currently adapted for the QQQ asset with 30/60min timeframe.
For other assets may require new optimization
Properties visible in this publication
• Initial capital 25000
• Base currency Default
• Default order size method percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Honest limitations and failure modes
• Past results do not guarantee future outcomes
• Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency
• Gap heavy symbols may benefit from the MAD Z normalization
• Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context
• Session time is the exchange time of the chart
• If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference
Open source reuse and credits
• None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank
• Method and fusion are original in construction and disclosure
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Strategy add on block
Strategy notice
Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used.
Entries and exits
• Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero
• Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short
• Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed
• Tie handling. Not applicable in this version because there are no fixed stops or targets
Position sizing
• Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice
Properties used on the published chart
• Initial capital 25000
• Base currency Default
• Default order size percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Dataset and sample size
• Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour
• Trade count in sample 324 on the example chart
Release notes template for future updates
Version 1.1.
• Add alertcondition lines for long, short, and exit short
• Add optional table with component readouts
• Add optional stop model with a distance unit expressed as ATR or a percent of price
Notes. Backward compatibility Yes. Inputs migrated Yes.
Universal Regime Alpha Thermocline StrategyCurrents settings adapted for BTCUSD Daily timeframe
This description is written to comply with TradingView House Rules and Script Publishing Rules. It is self contained, in English first, free of advertising, and explains originality, method, use, defaults, and limitations. No external links are included. Nothing here is investment advice.
0. Publication mode and rationale
This script is published as Protected . Anyone can add and test it from the Public Library, yet the source code is not visible.
Why Protected
The engine combines three independent lenses into one regime score and then uses an adaptive centering layer and a thermo risk unit that share a common AAR measure. The exact mapping and interactions are the result of original research and extensive validation. Keeping the implementation protected preserves that work and avoids low effort clones that would fragment feedback and confuse users.
Protection supports a single maintained build for users. It reduces accidental misuse of internal functions outside their intended context which might lead to misleading results.
1. What the strategy does in one paragraph
Universal Regime Alpha Thermocline builds a single number between zero and one that answers a practical question for any market and timeframe. How aligned is current price action with a persistent directional regime right now. To answer this the script fuses three views of the tape. Directional entropy of up versus down closes to measure unanimity.
Convexity drift that rewards true geometric compounding and penalizes drag that comes from chop where arithmetic pace is high but growth is poor.
Tail imbalance that counts decisive bursts in one direction relative to typical bar amplitude. The three channels are blended, optionally confirmed by a higher timeframe, and then adaptively centered to remove local bias. Entries fire when the score clears an entry gate. Exits occur when the score mean reverts below an exit gate or when thermo stops remove risk. Position size can scale with the certainty of the signal.
2. Why it is original and useful
It mixes orthogonal evidence instead of leaning on a single family of tools. Many regime filters depend on moving averages or volatility compression. Here we add an information view from entropy, a growth view from geometric drift, and a structural view from tail imbalance.
The drift channel separates growth from speed. Arithmetic pace can look strong in whipsaw, yet geometric growth stays weak. The engine measures both and subtracts drag so that only sequences with compounding quality rise.
Tail counting is anchored to AAR which is the average absolute return of bars in the window. This makes the threshold self scaling and portable across symbols and timeframes without hand tuned constants.
Adaptive centering prevents the score from living above or below neutral for long stretches on assets with strong skew. It recovers neutrality while still allowing persistent regimes to dominate once evidence accumulates.
The same AAR unit used in the signal also sets stop distance and trail distance. Signal and risk speak the same language which makes the method portable and easier to reason about.
3. Plain language overview of the math
Log returns . The base series is r equal to the natural log of close divided by the previous close. Log return allows clean aggregation and makes growth comparisons natural.
Directional entropy . Inside the lookback we compute the proportion p of bars where r is positive. Binary entropy of p is high when the mix of up and down closes is balanced and low when one direction dominates. Intensity is one minus entropy. Directional sign is two times p minus one. The trend channel is zero point five plus one half times sign times intensity. It lives between zero and one and grows stronger as unanimity increases.
Convexity drift with drag . Arithmetic mean of r measures pace. Geometric mean of the price ratio over the window measures compounding. Drag is the positive part of arithmetic minus geometric. Drift raw equals geometric minus drag multiplier times drag. We then map drift through an arctangent normalizer scaled by AAR and a nonlinearity parameter so the result is stable and remains between zero and one.
Tail imbalance . AAR equals the average of the absolute value of r in the window. We count up tails where r is greater than aar_mult times AAR and down tails where r is less than minus aar_mult times AAR. The imbalance is their difference over their total, mapped to zero to one. This detects directional impulse flow.
Fusion and centering . A weighted average of the three channels yields the raw score. If a higher timeframe is requested, the same function is executed on that timeframe with lookahead off and blended with a weight. Finally we subtract a fraction of the rolling mean of the score to recover neutrality. The result is clipped to the zero to one band.
4. Entries, exits, and position sizing
Enter long when score is strictly greater than the entry gate. Enter short when score is strictly less than one minus the entry gate unless direction is restricted in inputs.
Exit a long when score falls below the exit gate. Exit a short when score rises above one minus the exit gate.
Thermo stops are expressed in AAR units. A long uses the maximum of an initial stop sized by the entry price and AAR and a trail stop that references the running high since entry with a separate multiple. Shorts mirror this with the running low. If the trail is disabled the initial stop is active.
Cooldown is a simple bar counter that begins when the position returns to flat. It prevents immediate re entry in churn.
Dynamic position size is optional. When enabled the order percent of equity scales between a floor and a cap as the score rises above the gate for longs or below the symmetric gate for shorts.
5. Inputs quick guide with recommended ranges
Every input has a tooltip in the script. The same guidance appears here for fast reading.
Core window . Shared lookback for entropy, drift, and tails. Start near 80 on daily charts. Try 60 to 120 on intraday and 80 to 200 for swing.
Entry threshold . Typical range 0.55 to 0.65 for trend following. Faster entries 0.50 to 0.55.
Exit threshold . Typical range 0.35 to 0.50. Lower holds longer yet gives back more.
Weight directional entropy . Starting value 0.40. Raise on markets with clean persistence.
Weight convexity drift . Starting value 0.40. Raise when compounding quality is critical.
Weight tail imbalance . Starting value 0.20. Raise on breakout prone markets.
Tail threshold vs AAR . Typical range 1.0 to 1.5 to count decisive bursts.
Drag penalty . Typical range 0.25 to 0.75. Higher punishes chop more.
Nonlinearity scale . Typical range 0.8 to 2.0. Larger compresses extremes.
AAR floor in percent . Typical range 0.0005 to 0.002 for liquid instruments. This stabilizes the math during quiet regimes.
Adaptive centering . Keep on for most symbols. Center strength 0.40 to 0.70.
Confirm timeframe optional . Leave empty to disable. If used, try a multiple between three and five of the chart timeframe with a blend weight near 0.20.
Dynamic position size . Enable if you want size to reflect certainty. Floor and cap define the percent of equity band. A practical band for many accounts is 0.5 to 2.
Cooldown bars after exit . Start at 3 on daily or slightly higher on shorter charts.
Thermo stop multiple . Start between 1.5 and 3.0 on daily. Adjust to your tolerance and symbol behavior.
Thermo trailing stop and Trail multiple . Trail on locks gains earlier. A trail multiple near 1.0 to 2.0 is common. You can keep trail off and let the exit gate handle exits.
Background heat opacity . Cosmetic. Set to taste. Zero disables it.
6. Properties used on the published chart
The example publication uses BTCUSD on the daily timeframe. The following Properties and inputs are used so everyone can reproduce the same results.
Initial capital 100000
Base currency USD
Order size 2 percent of equity coming from our risk management inputs.
Pyramiding 0
Commission 0.05 percent
Slippage 10 ticks in the publication for clarity. Users should introduce slippage in their own research.
Recalculate after order is filled off. On every tick off.
Using bar magnifier on. On bar close on.
Risk inputs on the published chart. Dynamic position size on. Size floor percent 2. Size cap percent 2. Cooldown bars after exit 3. Thermo stop multiple 2.5. Thermo trailing stop off. Trail multiple 1.
7. Visual elements and alerts
The score is painted as a subtle dot rail near the bottom. A background heat map runs from red to green to convey regime strength at a glance. A compact HUD at the top right shows current score, the three component channels, the active AAR, and the remaining cooldown. Four alerts are included. Long Setup and Short Setup on entry gates. Exit Long by Score and Exit Short by Score on exit gates. You can disable trading and use alerts only if you want the score as a risk switch inside a discretionary plan.
8. How to reproduce the example
Open a BTCUSD daily chart with regular candles.
Add the strategy and load the defaults that match the values above.
Set Properties as listed in section 6.(they are set by default) Confirm that bar magnifier is on and process on bar close is on.
Run the Strategy Tester. Confirm that the trade count is reasonable for the sample. If the count is too low, slightly lower the entry threshold or extend history. If the count is excessively high, raise the threshold or add a small cooldown.
9. Practical tuning recipes
Trend following focus . Raise the entry threshold toward 0.60. Raise the trend weight to 0.50 and reduce tail weight to 0.15. Keep drift near 0.35 to retain the growth filter. Consider leaving the trail off and let the exit threshold manage positions.
Breakout focus . Keep entry near 0.55. Raise tail weight to 0.35. Keep aar_mult near 1.3 so only decisive bursts count. A modest cooldown near 5 can reduce immediate false flips after the first burst bar.
Chop defense . Raise drag multiplier to 0.70. Raise exit threshold toward 0.48 to recycle capital earlier. Consider a higher cooldown, for example 8 to 12 on intraday.
Higher timeframe blend . On a daily chart try a weekly confirm with a blend near 0.20. On a five minute chart try a fifteen minute confirm. This moderates transitions.
Sizing discipline . If you want constant position size, set floor equal to cap. If you want certainty scaling, set a band like 0.5 to 2 and monitor drawdown behavior before widening it.
10. Strengths and limitations
Strengths
Self scaling unit through AAR makes the tool portable across markets and timeframes.
Blends evidence that target different failure modes. Unanimity, growth quality, and impulse flow rarely agree by chance which raises confidence when they align.
Adaptive centering reduces structural bias at the score level which helps during regime flips.
Limitations
In very quiet regimes AAR becomes small even with a floor. If your symbol is thin or gap prone, raise the floor a little to keep stops and drift mapping stable.
Adaptive centering can delay early breakout acceptance. If you miss starts, lower center strength or temporarily disable centering while you evaluate.
Tail counting uses a fixed multiple of AAR. If a market alternates between very calm and very violent weeks, a single aar_mult may not capture both extremes. Sweep this parameter in research.
The engine reacts to realized structure. It does not anticipate scheduled news or liquidity shocks. Use event awareness if you trade around releases.
11. Realism and responsible publication
No promises or projections of performance are made. Past results never guarantee future outcomes.
Commission is set to 0.05 percent per round which is realistic for many crypto venues. Adjust to your own broker or exchange.
Slippage is set at 10 in the publication . Introduce slippage in your own tests or use a percent model.
Position size should respect sustainable risk envelopes. Risking more than five to ten percent per trade is rarely viable. The example uses a fixed two percent position size.
Security calls use lookahead off. Standard candles only. Non standard chart types like Heikin Ashi or Renko are not supported for strategies that submit orders.
12. Suggested research workflow
Begin with the balanced defaults. Confirm that the trade count is sensible for your timeframe and symbol. As a rough guide, aim for at least one hundred trades across a wide sample for statistical comfort. If your timeframe cannot produce that count, complement with multiple symbols or run longer history.
Sweep entry and exit thresholds on a small grid and observe stability. Stability across windows matters more than the single best value.
Try one higher timeframe blend with a modest weight. Large weights can drown the signal.
Vary aar_mult and drag_mult together. This tunes the aggression of breakouts versus defense in chop.
Evaluate whether dynamic size improves risk adjusted results for your style. If not, set floor equal to cap for constancy.
Walk forward through disjoint segments and inspect results by regime. Bootstrapping or segmented evaluation can reveal sensitivity to specific periods.
13. How to read the HUD and heat map
The HUD presents a compact view. Score is the current fused value. Trend is the directional entropy channel. Drift is the compounding quality channel. Tail is the burst flow channel. AAR is the current unit that scales stops and the drift map. CD is the cooldown counter. The background heat is a visual aid only. It can be disabled in inputs. Green zones near the upper band show alignment among the channels. Muted colors near the mid band show uncertainty.
14. Frequently asked questions
Can I use this as a pure indicator . Yes. Disable entries by restricting direction to one side you will not trade and use the alerts as a regime switch.
Will it work on intraday charts . Yes. The AAR unit scales with bar size. You will likely reduce the core window and increase cooldown slightly.
Should I enable the adaptive trail . If you wish to lock gains sooner and accept more exits, enable it. If you prefer to let the exit gate do the heavy lifting, keep it off.
Why do I sometimes see a green background without a position . Heat expresses the score. A position also depends on threshold comparisons, direction mode, and cooldown.
Why is Order size set to one hundred percent if dynamic size is on . The script passes an explicit quantity percent on each entry. That explicit quantity overrides the property. The property is kept at one hundred percent to avoid confusion when users later disable dynamic sizing.
Can I combine this with other tools on my chart . You can, yet for publication the chart is kept clean so users and moderators can see the output clearly. In your private workspace feel free to add other context.
15. Concepts glossary
AAR . Average absolute return across the lookback. Serves as a unit for tails, drift scaling, and stops.
Directional entropy . A measure of uncertainty of up versus down closes. Low entropy paired with a directional sign signals unanimity.
Geometric mean growth . Rate that preserves the effect of compounding over many bars.
Drag . The positive difference between arithmetic pace and geometric growth. Larger drag often signals churn that looks active but fails to compound.
Thermo stops . Stops expressed in the same AAR unit as the signal. They adapt with volatility and keep risk and signal on a common scale.
Adaptive centering . A bias correction that recenters the fused score around neutral so the meter does not drift due to persistent skew.
16. Educational notice and risk statement
Markets involve risk. This publication is for education and research. It does not provide financial advice and it is not a recommendation to buy or sell any instrument. Use realistic costs. Validate ideas with out of sample testing and with conservative position sizing. Past performance never guarantees future results.
17. Final notes for readers and moderators
The goal of this strategy is clarity and portability. Clarity comes from a single score that reflects three independent features of the tape. Portability comes from self scaling units that respect structure across assets and timeframes. The publication keeps the chart clean, explains the math plainly, lists defaults and Properties used, and includes warnings where care is required. The code is protected so the implementation remains consistent for the community while the description remains complete enough for users to understand its purpose and for moderators to evaluate originality and usefulness. If you explore variants, keep them self contained, explain exactly what they contribute, publish in English first, and treat others with respect in the comments.
Load the strategy on BTCUSD daily with the defaults listed above and study how the score transitions across regimes. Then adjust one lever at a time. Observe how the trend channel, the drift channel, and the tail channel interact during starts, pauses, and reversals. Use the alerts as a risk switch inside your own process or let the built in entries and exits run if you prefer an automated study. The intent is not to promise outcomes. The intent is to give you a robust meter for regime strength that travels well across markets and helps you structure decisions with more confidence.
Thank you for your time to read all of this
PulseGrid Universal Scalper - Adaptive Pulse and Symmetric SpansInstrument agnostic. Works on any symbol and timeframe supported by TradingView.
Message or hit me up in chat for full access .
Purpose and scope
PulseGrid is a short timeframe strategy designed to read intrabar structure and recent path so that entries align with actionable momentum and context. The strategy is private. The description below provides all the information needed to understand how it behaves, how it sizes risk, how to tune it responsibly, and how to evaluate results without making unrealistic claims. The design is instrument agnostic. It runs on any asset class that prints open high low close bars on TradingView. That includes commodities such as Gold and WTI, currencies, crypto, equity indices, and single stocks. Performance will always depend on the symbol’s liquidity, spread, slippage, and session structure, which is why the description focuses on principles and safe parameter ranges instead of hard promises.
What the strategy does at a glance
It builds a composite entry signal named Pulse from five normalized bar features that reflect short term pressure and follow through.
It applies regime guards that keep the strategy inactive when the tape is either too quiet, too bursty, or too directionally random.
It optionally uses a directional filter where a fast and a slow exponential average must agree and their gap must be material relative to recent true range.
When a signal is allowed, risk is sized using symmetric spans that come from nearby untraded price distances above and below the market. The strategy sets a single stop and a single take profit from those spans.
Lines for entry, stop, and take profit are drawn on the chart. A compact on chart table shows trade counts, win rate, average R per trade, and profit factor for all trades, longs only, and shorts only.
This combination yields entries that are reactive but not chaotic, and risk lines that respect the market’s recent path instead of generic pip or point targets.
Why the design is original and useful
The core originality is the union of a composite entry that adapts to volatility and a geometry based risk model. The entry uses five different viewpoints on the same bar space instead of relying on a single technical indicator. The risk model uses spans that come from actual untraded distance rather than fixed multipliers of a generic volatility measure. The result is a framework that is simple to read on a chart and simple to evaluate, yet it avoids the traps of curve fitting to one symbol or one month of data. Because everything is normalized locally, the same logic translates across asset classes with only modest tuning.
The Pulse composite in detail
Pulse is a weighted blend of the following normalized features.
Impulse imbalance. The script sums upward and downward impulses over a short window. An upward impulse is the extension of highs relative to the prior bar. A downward impulse is the extension of lows relative to the prior bar. The net imbalance, scaled by the local range, captures whether extension pressure is building or fading.
Wick and close location. Inside each bar, the distance between the close and the extremes carries information about rejection or acceptance. A bar that closes near the high with relatively heavier lower wick suggests upward acceptance. A bar that closes near the low with heavier upper wick suggests downward acceptance. A weight controls the contribution of wick skew versus close location so that users can favor reversal or momentum behaviour.
Shock touches. Within the recent range window, touches that occur very near the top decile or bottom decile are marked. A short sliding window counts recent shocks. Frequent top shocks in a rising context suggest supply tests. Frequent bottom shocks in a declining context suggest demand tests. The count is normalized by window length.
Breakout ledger. The script compares current extremes to lagged extremes and keeps a simple count of recent upside and downside breakouts. The difference behaves as a short term polarity meter.
Curvature. A simple second difference in closing price acts as a curvature term. It is normalized by the recent maximum of absolute one bar returns so that the value remains bounded and comparable to other terms.
Pulse is smoothed over a fraction of the main signal length. Smoothing removes impulse spikes without destroying the quick reaction that scalpers need. The absolute value of smoothed Pulse can be used with an adaptive gate so that only the top percentile of energy for the recent environment is eligible for entries. A small floor prevents accidental entries during very quiet periods.
Regime guards that keep the strategy selective
Three guards must all pass before any entry can occur.
Auction Balance Factor. This is the proportion of closes that land inside a mid band of the prior bar’s high to low range. High values indicate balanced chop where breakouts tend to fail. Low values indicate directional conditions. The strategy requires ABF to sit below a user chosen maximum.
Dispersion via a Gini style measure on absolute returns. Very low dispersion means bars are small and uniform. Very high dispersion means a few outsized bars dominate and slippage risk can be elevated. The strategy allows the user to require the dispersion measure to remain inside a band that reflects healthy activity.
Binary entropy of direction. Over the core window, the proportion of up closes is used to compute a simple entropy. Values near one indicate coin flip behaviour. Values near zero indicate one sided sequences. The guard requires entropy below a ceiling so that random directionality does not produce noise entries.
An optional directional filter asks that a fast and a slow exponential average agree on direction and that their gap, when divided by an average true range, exceed a threshold. This filter can be enabled on symbols that trend cleanly and disabled when the composite entry is already selective enough.
Risk sizing with symmetric spans
Instead of fixed points or a pure ATR multiplier, the strategy sizes stops and targets from a pair of spans. The upward span reflects recent untraded distance above the market. The downward span reflects recent untraded distance below the market. Each span is floored by a fallback that comes from the maximum of a short simple range average and a standard average true range. A tick based floor prevents microscopic stops on instruments with high tick precision. An asymmetry cap prevents one span from becoming many times larger than the other. For long entries the stop is a multiple of the downward span and the target is a multiple of the upward span. For short entries the stop is a multiple of the upward span and the target is a multiple of the downward span. This creates a risk box that is symmetric by construction yet adaptive to recent voids and gaps.
Execution, ties, and housekeeping
Entries evaluate at bar close. Exits are tested from the next bar forward. If both stop and target are hit within the same bar, the outcome can be resolved in a consistent way that favors the stop or the target according to a single user setting. A short cooldown in bars prevents flip flops. Users can restrict entries to specific sessions such as London and New York. The chart renders entry, stop, and target lines for each trade so that every action is visible. The table in the top right shows trade counts, take profit and stop counts, win rate, average R per trade, and profit factor for the whole set and by direction.
Defaults and responsible backtesting
The default properties in the script use a realistic initial capital and commission value. Users should also set slippage in the strategy properties to reflect their broker and symbol. Small timeframe trading is sensitive to friction and the strategy description does not claim immunity to that reality. The strategy is intended to be tested on a dataset that produces a meaningful sample of trades. A sample in the range of a hundred trades or more is preferred because variance in short samples can be large. On thin symbols or periods with little regular trading, users should either change timeframe, change sessions, or use more selective thresholds so that the sample contains only liquid scenarios.
Universal usage across markets
The strategy is universal by design. It will run and produce lines on any open high low close series on TradingView. The composite entry is made of normalized parts. The regime guards use proportions and bounded measures. The spans use untraded distance and range floors measured in the local price scale. This allows the same logic to function on a currency pair, a commodity, an index future, a stock, or a crypto pair. What changes is calibration.
A safe approach for universal use is as follows.
Start with the default signal length and wick weight.
If the chart prints many weak signals, enable the directional filter and raise the normalized gap threshold slightly.
If the chart is too quiet, lower the adaptive percentile or, with adaptive off, lower the fixed pulse threshold by a small amount.
If stops are too tight in quiet regimes, raise the fallback span multiplier or raise the minimum tick floor in ticks.
If you observe long one sided days, lower the maximum entropy slightly so that entries only occur when directionality is genuine rather than alternating.
Because the logic is bounded and local, these simple steps carry over across symbols. That is why the strategy can be used literally on any asset that you can load on a TradingView chart. The code does not depend on a specific tick size or a specific exchange calendar. It will still remain true that symbols with higher spread or fewer regular trading hours demand stricter thresholds and larger floors.
Suggested parameter ranges for common cases
These ranges are guidelines for one to five minute bars. They are not promises of performance. They reflect the balance between having enough signals to learn from and keeping noise controlled.
Signal length between 18 and 34 for liquid commodities and large capitalization equities.
Wick weight between 0.30 and 0.50 depending on whether you want reversal recognition or close momentum.
Adaptive gate percentile between 85 and 93 when adaptive is enabled. Fixed threshold between 0.10 and 0.18 when adaptive is disabled. Use a non zero floor so very quiet periods still require some energy.
Auction Balance Factor maximum near 0.70 for symbols with clear session bursts. Slightly higher if you prefer to include more balanced prints.
Dispersion band with a lower bound near 0.18 and an upper bound near 0.68 for most session instruments. Tighten the band if you want to skip very bursty days or very flat days.
Entropy maximum near 0.90 so coin flip phases are filtered. Lower the ceiling slightly if the symbol whipsaws frequently.
Stop multiplier near one and take profit multiplier between two and three for a single target approach. Larger target multipliers reduce hit rate and lengthen holding time.
These are safe starting points across commodities, currencies, indices, equities, and crypto. From there, small increments are preferred over dramatic changes.
How to evaluate responsibly
A clean chart and a direct test process help avoid confusion. Use standard candles for signals and exits. If you use a non standard chart type such as Heikin Ashi or Renko, do so only for visualization and not for the strategy’s signal computation, as those chart types can produce unrealistic fills. Turn off other indicators on the published chart unless they are needed to demonstrate a specific property of this strategy. When you post results or discuss outcomes, include the symbol, timeframe, commission and slippage settings, and the session settings used. This makes the context clear and avoids misleading readers.
When you look at results, consider the following.
The distribution of R per trade. A positive average R with a moderate profit factor suggests that exits are sized appropriately for the symbol.
The balance between long and short sides. The HUD table separates the two so you can see if one side carries the edge for that symbol.
The sensitivity to the tie preference. If many bars hit both stop and take profit, the market is chopping inside the risk box and you may need larger floors or stricter regime guards.
The session effect. Session hours matter for many instruments. Align your session filter with where liquidity and volatility concentrate.
Known limitations and honest warnings
PulseGrid is not a guarantee of future profit. It is a systematic way to read short term structure and to size risk in a way that reflects recent path. It assumes that the data feed reflects the exchange reality. It assumes that slippage and spread are non zero and uses explicit commission and user provided slippage to approximate that. It does not place multiple targets. It does not trail stops. It is not a high frequency system and does not attempt to model queue priority or microsecond fills. On illiquid symbols or very short timeframes outside regular hours, signals will be less reliable. Users are responsible for choosing realistic settings and for evaluating whether the symbol’s conditions are suitable.
First use checklist
Load the symbol and timeframe you care about.
If the instrument has clear sessions, turn on the session filter and select realistic London and New York hours or other sessions relevant to the instrument.
Set commission and slippage in the strategy properties to values that match your broker or exchange.
Run the strategy with defaults. Look at the HUD summary and the lines.
Decide whether to enable the directional filter. If you see frequent reversals around the entry line, enable it and raise the normalized gap threshold slightly.
Adjust the adaptive gate. If the chart floods, raise the percentile. If the chart starves, lower it or use a slightly lower fixed threshold.
Adjust the fallback span multiplier and tick floor so that stops are never microscopic.
Review per session performance. If one session underperforms, restrict entries to the better one.
This simple process takes minutes and transfers to any other symbol.
Why this script is private
The source remains private so that the underlying method and its implementation details are not copied or republished. The description here is complete and self contained so that users can understand the purpose, originality, usage, and limitations without needing to inspect the source. Privacy does not change the strategy’s on chart behavior. It only protects the specific coding details.
Guarantee and compliance statements
This description does not contain advertising, solicitations, links, or contact information. It does not make performance promises. It explains how the script is original and how it works. It also warns about limitations and the need for realistic assumptions. The strategy is not investment advice and is not created only for qualified investors. It can be tested and used for educational and research purposes. Users should read TradingView’s documentation on script properties and backtesting. Users should avoid non standard chart types for signal computation because those produce unrealistic results. Users should select realistic account sizes and friction settings. Users should not post claims without showing the settings used.
Closing summary
PulseGrid is a compact framework for short timeframe trading that combines a composite entry built from multiple normalized bar features with a symmetric span model for risk. The entry adapts to volatility. The regime guards keep the strategy inactive when the tape is either too quiet or too erratic. The risk geometry respects recent untraded spans instead of arbitrary distances. The entire design is instrument agnostic. It will run on any symbol that TradingView supports and it will behave consistently across asset classes with modest tuning. Use it with a clean chart, realistic friction, and enough trades to make your evaluation meaningful. Use sessions if the instrument concentrates activity in specific hours. Adjust one control at a time and prefer small increments. The goal is not to find a magic parameter. The goal is to maintain a stable rule set that reads market structure in a way you can trust and audit.
Daytrade Forex Scalper TwinPulse Auction Timer IndicatorWhat this indicator is
TwinPulse Auction Timer is a multi component execution aid designed for liquid markets. It looks for two families of opportunities
Breakouts that leave a compression area after a fresh sweep
Reversals that trigger after a sweep with strong wick polarity
It does not try to predict future prices. It measures present auction conditions with transparent rules and shows you when those conditions align. You get a simple table that says LONG SHORT or WAIT, optional session shading, clean entry and exit level visuals, and alerts you can wire to your workflow.
Why it is different
Most tools show a single signal. TwinPulse combines several independent signals into an Edge Score that you can tune. The components are
• Pulse. A signed measure of wick asymmetry with candle body direction
• Compression. Current true range compared with an average range
• Sweep timer. Bars elapsed since the most recent sweep of a prior high or low
• Bias. Direction of a higher timeframe candle
• Regime. Efficiency ratio and the relation of micro to macro volatility
• Location. Distance from the daily anchored VWAP
• Session. London and New York filter by time windows
Each component is visible in the inputs and in the table so you can understand why a suggestion appears. The script uses request.security() with lookahead off in all calls so it does not peek into the future. Shapes may move while a bar is open since price is still forming. They stop moving when the bar closes.
What you will see on the chart
• L and S shapes on entry bars
• An Exit shape at the price where a stop or the runner target would have been hit
• Four horizontal lines while a trade is active
Entry
Stop
TP1 at one R
TP2 at the runner target expressed in R
• Labels anchored to each line so you can instantly read Entry SL TP1 and TP2 with current values
• Optional shading during your session windows
• Optional daily VWAP line
The table in the top right shows
Action LONG SHORT IN LONG IN SHORT or WAIT
Session ON or OFF
Bias UP DOWN or FLAT
Pulse value
Compression value
Edge L percent and Edge S percent
How it works in detail
Pulse
For each bar the script measures up wick minus down wick divided by range and multiplies that by the sign of the candle body. The result is averaged with pulse_len. Positive numbers indicate aggressive buying. Negative numbers indicate aggressive selling. You control the minimum absolute value with pulse_thr.
Compression
Compression is the ratio of current range to an average range. You can choose the range basis. HL SMA uses simple high minus low smoothed by range_len. ATR uses classic True Range smoothed by atr_len. Values below comp_thr indicate a coil.
Sweeps and the timer
A sweep occurs when price trades beyond the highest high or lowest low seen in the previous sweep_len bars. A strict sweep requires a close back inside that prior range. The timer measures how many bars have elapsed since the last sweep. Breakout setups require the timer to exceed timer_thr.
Bias on a confirmation timeframe
A higher timeframe candle is read with confirm_tf. If close is above open bias is UP. If close is below open bias is DOWN. This keeps breakouts aligned with the prevailing drift.
Regime filters
Efficiency ratio measures the straight line change over the sum of absolute bar to bar changes over er_len. It rises in trendy conditions and falls in noise. Minimum efficiency is controlled by er_min.
Micro to macro volatility ratio compares a short lookback average range with a longer lookback average range using your chosen basis. For breakouts you usually want micro volatility to be near or above macro hence mvr_min. For reversals you often want micro volatility that is not overheated relative to macro hence mvr_max_rev.
VWAP distance gate
Daily anchored VWAP is rebuilt from the open of each session. The script computes the absolute distance from VWAP in units of your average range and requires that distance to exceed vwap_dist_thr when use_vwap_gate is true. This keeps entries away from the mean.
Edge Score
Each gate contributes a weight that you control. The script sums weights of the satisfied gates and divides by the sum of all weights to produce an Edge percent for long and an Edge percent for short. You can then require a minimum Edge percent using edge_min_pct. This turns the indicator into a step by step checklist that you can tune to your taste.
Using the indicator step by step
Choose markets and timeframes
The logic is designed for liquid instruments. Major currency pairs, index futures and cash index CFDs, and the most liquid crypto pairs work well. On intraday use one to fifteen minutes for signals and fifteen to sixty minutes for confirmation. On swing use one hour to one day for signals and one day for confirmation.
Decide on entry mode
Breakouts require a compression area and a sweep timer. Reversals require a strict sweep and a strong pulse. If you are unsure leave the default which allows both.
Pick a range basis
For FX and crypto HL SMA is often stable. For indices and single name equities with gaps ATR can adapt better. If results look too reactive increase the window. If results are too slow reduce it.
Tune regime filters
If you trade trend continuation raise er_min and mvr_min. If you trade counter rotation lower them and rely on the reversal path with the strict sweep condition.
Set the VWAP gate
Enabling it helps you avoid entries at the mean. Push the threshold higher on range bound days. Reduce it in strong trend days.
Table driven decision
Watch Action and the Edge percents. If the script says WAIT you can read Pulse and Compression to see what is missing. Often the best trades appear when both Edge percents are well separated and your session switch is ON.
Use the visuals
When a suggestion triggers you will see entry stop and targets. You can mirror the levels in your own workflow or use alerts.
Consider bar close
Signals are computed in real time. For a strict process you can wait until the bar closes to reduce noise.
Inputs explained with quick guidance
Setup
Signal TF chooses where the logic is computed. Leave blank to use the chart.
Confirm TF sets the higher timeframe for bias.
Session filter restricts signals to the London and New York windows you specify.
Invert flips long and short. It is useful on inverse instruments.
Logic options
Entry mode allows Breakouts Reversals or Both.
Average range basis selects HL SMA or ATR.
ATR length is used when ATR is selected.
Pulse source can be Regular OHLC or Heikin Ashi. Heikin Ashi smooths noisy series, but the script still runs on regular bars and you should publish and use it on standard candles to respect the platform guidance.
Core numeric settings
Sweep lookback controls the size of the liquidity pool targeted by the sweep condition.
Pulse window smooths the wick polarity measure.
Average range window controls your base range when you use HL SMA.
Pulse threshold sets the minimum polarity required.
Compression threshold sets the maximum current range relative to average to consider the market coiled.
Expansion timer bars sets how much time has passed since the last sweep before you allow a breakout.
Regime filters
Efficiency ratio length and minimum value keep you out of aimless drift.
Micro and Macro range lengths feed the micro to macro ratio.
Minimum micro to macro for breakouts and maximum micro to macro for reversals steer the two entry families.
VWAP gate and distance threshold keep you away from the mean.
Levels and trade management visuals
Runner target in R sets TP2 as a multiple of initial risk.
Stop distance as average range multiple sets initial risk size for the visuals.
Move stop to entry after one R touch turns on break even logic once price has traveled one risk unit.
Trail buffer as R fraction uses the last sweep as an anchor and keeps a dynamic stop at a chosen fraction of R beyond it.
Cooldown after exit prevents immediate re entries.
Edge Score
Weights for pulse compression timer bias efficiency ratio micro to macro VWAP gate and session let you align the checklist with your style.
Minimum Edge percent to suggest applies a final filter to LONG or SHORT suggestions.
UI
Table and markers switch the compact dashboard and the shapes.
TP and SL lines and labels draw and name each level.
TP1 partial label percent is printed in the TP1 label for clarity.
Session shading helps with focus.
Daily VWAP line is optional.
Alerts
The script provides alerts for Long Short Exit and for Edge percent crossing the threshold on either side. Use them to drive notifications or to sync with webhooks and your broker integration. Alerts trigger in real time and will repaint during a bar. For conservative use trigger on bar close.
Recommended presets
Intraday trend continuation
Confirm TF fifteen minutes
Entry mode Breakouts
Range basis HL SMA
Pulse threshold near 0.10
Compression threshold near 0.60
Timer around 18
Minimum efficiency ratio near 0.20
Minimum micro to macro near 1.00
VWAP gate enabled with distance near 0.35
Edge minimum 50 or higher
Intraday mean reversion at sweeps
Entry mode Reversals
Pulse source Regular OHLC
Compression threshold can be a little higher
Maximum micro to macro near 1.60
Efficiency ratio minimum lower near 0.12
VWAP gate enabled
Edge minimum 40 to 60
Swing trend continuation
Signal TF one hour
Confirm TF one day
Range basis ATR
ATR length around 14
Average range window 20 to 30
Efficiency ratio minimum near 0.18
Micro to macro windows 12 and 60
Edge minimum 50 to 70
These are starting points only. Your instrument and timeframe will require small adjustments.
Limitations and honest warnings
No indicator is perfect. TwinPulse will mark attractive conditions that do not always lead to profitable trades. During economic releases or very thin liquidity the assumptions behind compression and sweeps may fail. In strong gap environments the HL SMA basis may lag while ATR may overreact. Heikin Ashi pulse can help in choppy markets but it will lag during sharp reversals. Session times use the exchange time of your chart. If you switch symbol or exchange verify the windows.
Edge percent is not a probability of profit. It is the fraction of satisfied gates with your chosen weights. Two traders can set different weights and see different Edge readings on the same bar. That is the design. The score is a guide that helps you act with discipline.
This indicator does not place orders or manage real risk. The lines and labels show a model entry a model stop and two model targets built from the average range at entry and from recent swing points. Use them as references and not as hard rules. Always test on historical data and demo first. Past results do not guarantee anything in the future.
Credits and originality
All code in this publication is original and written for this indicator. The concept of the efficiency ratio originates from Perry Kaufman. The use of a daily anchored volume weighted average price is a standard industry tool. The specific combination of pulse from wick polarity strict sweep timing compression and the tunable Edge Score is unique to this script at the time of publication. If you reuse parts of the open source code in your own work remember to credit the author and contribute meaningful improvements.
How to read the table at a glance
Action reflects your current state.
IN LONG or IN SHORT appears while a trade is active.
LONG or SHORT appears when conditions for entry are met and the Edge threshold is satisfied.
WAIT appears when at least one gate is missing.
Session shows ON during your chosen windows.
Bias shows the color of the confirmation candle.
Pulse is the smoothed polarity number.
Comp shows current range divided by the average range. Values below one mean compression.
Edge L percent and Edge S percent show the long and short checklists as percents.
Final thoughts
Markets move because orders accumulate at certain prices and at certain times. The indicator tries to measure two things that often matter at those turning points. One is the existence of a hidden imbalance revealed by wick polarity and by sweeps of prior extremes. The other is the presence of energy stored in a coil that can release in the direction of a drift. Neither force guarantees profit. Together they can improve your selection and your timing.
Use the defaults for a few days so you learn the personality of the signals. After that adjust one group at a time. Start with the session filter and the Edge threshold. Then tune compression and the timer. Finally adjust the regime filters. Keep notes. You will learn which weights matter for your market and timeframe. The result is a process you can apply with consistency.
Disclaimer
This script and description are for education and analysis. They are not investment advice and they do not promise future results. Use at your own risk. Test thoroughly on historical data and in simulation before considering any live use.
50% Fib Trend Cloud + ATR BandsThis indicator plots two structural 50% fibonacci midpoints from recent confirmed 'left/right' swings that form a *cloud* of equilibrium, then adds a rolling 50% fibonacci range midpoint based on a lookback window that's wrapped in ATR bands. Importantly, it solves a specific trading problem:
Structural midpoints (macro context) are powerful but can lag when price escapes prior ranges. Enter rolling 50% fib + ATR ➡️ which restores real-time balance & tolerance (micro context). Together they show where price is balanced structurally, where it’s balanced right now, and how much volatility to tolerate before acting.
➖➖➖
🔑 Why this is different
Most tools either draw a single midpoint (ex., daily 50%) or ATR bands around a moving average. This script fuses dual swing-based 50% midpoints (structure) + a rolling 50% with ATR (flow), so you don’t lose context when price escapes prior ranges. The cloud tells you who’s in control (fast vs. slow structure). The rolling 50% + ATR tells you how far is “too far” now.
➖➖➖
🧠 What it does (at a glance)
🔸Structural Equilibrium × 2 (Fib1/Fib2)
Two independent 50% midpoints formed from swing pivots (configurable Left/Right bars + optional smoothing). Their gap is the Midpoint Cloud = structural “fair value” zone.
🔸Rolling 50% + ATR Bands
A rolling highest/lowest window computes an always-current 50% rolling midpoint plot; ±ATR × length envelopes define a soft value area and over-stretch boundaries.
🔸Actionable Visuals
Optional fill between Fib1/Fib2, labels, and candle-overlay modes to instantly read regime (above both / below both / between).
🔸Smart Defaults
Timeframe-aware presets for L/R pivots & smoothing; full manual overrides available.
➖➖➖
⚙️ Calculations (plain-English)
🔸Pivot midpoints (Fib1 & Fib2):
1) Detect a swing using `Left/Right` bars
2) Take the swing’s high/low → compute 50%
3) (Optional) Smooth the line (SMA) to stabilize on noisy TFs
4) Repeat with a different sensitivity to get two distinct midpoints
🔸Rolling midpoint:
Highest High / Lowest Low over the last *N* bars → (HH + LL) / 2
🔸ATR levels:
`Upper = Rolling50 + ATR × Mult`, `Lower = Rolling50 − ATR × Mult`
(Typical: ATR length 14–21; Multipliers 2.236 for L1, 5.382 for L2)
➖➖➖
🤖 Auto-Configured Presets (with Manual Override)
💡Goal: make the midpoints “just work” on common timeframes while still letting you dial them in.
💡How Auto Presets work
When Auto Presets = ON, the script picks sensible L/R/S (Left bars / Right bars / Smoothing) for Fib Trend 1 and Fib Trend 2 based on chart timeframe.
🔸Fib 1 (fast) emphasizes *micro-structure* for quicker bias shifts.
🔸Fib 2 (slow) emphasizes *macro-structure* for anchor/bias context.
These defaults keep Fib 1 responsive without jitter and Fib 2 stable without lag.
➡️ Turn Auto Presets = OFF to take full control with the manual inputs described below.
➖➖➖
🛠 Manual Fib Midpoint Settings (when Auto = OFF)
💡Each midpoint uses three knobs:
🔸Pivot Left (L): bars to the left that must be lower/higher to qualify a swing
🔸Pivot Right (R): bars to the right that must be lower/higher to confirm the swing
🔸Smoothing (S): SMA period applied to the raw 50% midpoint (stabilizes noise)
5-Minute optimized defaults
🔸Fib Trend 1: `L21 / R5 / S55` → responsive local structure (entries/exits, re-balancing zones)
🔸Fib Trend 2: `L55 / R13 / S89` → broader structure (trend context, anchors/stops)
Timeframe guidance
🔸1m–3m: may feel a touch laggy → consider ~`L13 / R3 / S34`
🔸15m–1h: defaults remain strong → optionally ~`L34 / R8 / S89`
🔸4h+ : increase span for stability → `L89–144 / R13–21 / S144–233`
➡️ Rule of thumb: shorter L/R = faster detection, longer S = smoother line. Tune until Fib 1 captures the “active swing” and Fib 2 captures the “dominant swing” without whipsaw.
➖➖➖
🎛 Inputs (quick reference)
🔸Fib Trend 1/2: Source (High/Low/Close), Left/Right bars, Smoothing length, Show/Hide, Cloud fill toggle
🔸Rolling 50%: Lookback length, Price basis (Wicks/Close/HLC3/OHLC4), Plot scope (Full / Last N / None)
🔸ATR Bands: ATR length, Multipliers (L1/L2), Plot scope, Line width/colors
🔸Overlay & Labels: Candle overlay mode, Label padding/size, 50% centerline toggle, Plot widths
➖➖➖
🖍️ Candle Coloring & Overlay Modes
💡Purpose: make trend instantly visible on the candles and ATR levels.
1) Color Logic (dropdown)
🔸 Fib Midpoints — Colors by position of price vs. Fib 1 & Fib 2
🔸ATR Zones — Colors by which ATR zone price is in relative to the Rolling 50%
➡️ Price Reference: Choose the input used for the decision (Close, HL2, OHLC3, OHLC4).
➡️Tip: Close is crisp; HL2/OHLC variants are smoother.
2) Overlay Style (dropdown)
🔸 None — No visual change to candles
🔸 Bar Color — Uses `barcolor()` to tint built-in candles (this takes into account your Trading View settings, for instance if you have wicks set to white, they will show up as white with this setting)
🔸 PlotCandles — Draws unified custom candles (body, wick, border) with the same color for maximum clarity
💡Practical use
🔸 Pick Fib Midpoints to read structural bias at a glance (above/below/between the cloud).
🔸 Pick ATR Zones to read value vs. stretch around the Rolling 50% (mean-reversion vs. trend extension).
➖➖➖
📘 How to use
A) Trend confirmation
- Strong bullish bias when price holds above both structural mids; strong bearish when below both.
- Use the Rolling 50% + ATR as a dynamic re-entry zone: pullbacks that respect ATR(L1) often continue the prevailing trend.
B) Transition / mean reversion
- Inside the Cloud (between Fib1 & Fib2) treat behavior as neutralization/re-balancing; range tactics tend to outperform momentum plays.
- In ranges, fades near ±ATR around the rolling 50% can mark short-term edges.
C) Breakout context
- When price leaves the Cloud, the Rolling 50% keeps you anchored so price never feels “floating.” A clean hold outside ATR(L1/L2) suggests regime strength; quick re-entries hint at traps.
➖➖➖
🖼 Chart examples
➡️ Each snapshot shows how the Cloud (structure) and the Rolling 50% + ATR (flow) work together.
1) 1-Minute Downtrend – Cloud as Dynamic Ceiling
- The Cloud slopes down; pullbacks repeatedly fail under the Cloud’s underside.
- Rolling 50% (dashed mid) + ATR(L1) act as a reversion band: rallies stall near upper ATR and rotate lower.
2) 15-Minute Persistent Drift – Structure Guides, Flow Times Entries
- Long drift lower with Cloud overhead.
- Consolidations near the rolling mid resolve in the trend direction; ATR bands frame risk on each attempt.
3) 15-Minute Uptrend (BTC) – From Cloud Escape to Value Stair-Step
- After escaping the prior Cloud, rolling 50% + ATR establish a new higher value area.
- Pullbacks into ATR(L1) produce orderly stair-steps; Cloud remains supportive on deeper dips
4) 5-Minute BTC – Pullback to Value then Rotate
- Strong leg up; retrace tags lower ATR band and rotates back toward the rolling mid.
- Labels (Fib1/Fib2) make the structural context explicit for decision-making.
➖➖➖
🧪 Starter presets
- Intraday (5–15m): Fib1 ~ L21/R5 (smooth 5), Fib2 ~ L55/R13 (smooth 9) • Rolling = 55 • ATR = 14 • L1 = 2.5x, L2 = 5.0x
- Scalping: Shorten lookbacks & smoothing; keep ATR multipliers similar, or tighten L1.
- Swing: Lengthen all lookbacks; consider ATR length 21–28.
➖➖➖
🏁Final Word
This script is not just a visual tool, it’s a complete trend and structure framework. Whether you're looking for clean trend alignment, dynamic support/resistance, or early warning signs of a reversal, this system is tuned to help you react with confidence — not hindsight.
Rembember, no single indicator should be used in isolation. For best results, combine it with price action analysis, higher-timeframe context, and complementary tools like trendlines, moving averages etc Use it as part of a well-rounded trading approach to confirm setups — not to define them alone.
---
💡Turn logic into clarity. Structure into trades. And uncertainty into confidence.
Bitcoin Cycle History Visualization [SwissAlgo]BTC 4-Year Cycle Tops & Bottoms
Historical visualization of Bitcoin's market cycles from 2010 to present, with projections based on weighted averages of past performance.
-----------------------------------------------------------------
CALCULATION METHODOLOGY
Why Bottom-to-Bottom Cycle Measurement?
This indicator defines cycles as bottom-to-bottom periods. This is one of several valid approaches to Bitcoin cycle analysis:
- Focuses on market behavior (price bottoms) rather than supply schedule events (halving-to-halving)
- Bottoms may offer good reference points for some analytical purposes
- Tops tend to be extended periods that are harder to define precisely
- Aligns with how some traditional asset cycles are measured and the timing observed in the broader "risk-on" assets category
- Halving events are shown separately (yellow backgrounds) for reference
- Neither halving-based nor bottom-based measurement is inherently superior
Different analysts prefer different cycle definitions based on their analytical goals. This approach prioritizes observable market turning points.
Cycle Date Definitions
- Approximate monthly ranges used for each event (e.g., Nov 2022 bottom = Nov 1-30, 2022)
- Cycle 1: Jul 2010 bottom → Jun 2011 top → Nov 2011 bottom
- Cycle 2: Nov 2011 bottom → Dec 2013 top → Jan 2015 bottom
- Cycle 3: Jan 2015 bottom → Dec 2017 top → Dec 2018 bottom
- Cycle 4: Dec 2018 bottom → Nov 2021 top → Nov 2022 bottom
- Future cycles will be added as new top/bottom dates become firm
Duration Calculations
- Days = timestamp difference converted to days (milliseconds ÷ 86,400,000)
- Bottom → Top: days from cycle bottom to peak
- Top → Bottom: days from peak to next cycle bottom
- Bottom → Bottom: full cycle duration (sum of above)
Price Change Calculations
- % Change = ((New Price - Old Price) / Old Price) × 100
- Example: $200 → $19,700 = ((19,700 - 200) / 200) × 100 = 9,750% gain
- Approximate historical prices used (rounded to significant figures)
Weighted Average Formula
Recent cycles weighted more heavily to reflect the evolved market structure:
- Cycle 1 (2010-2011): EXCLUDED (too early-stage, tiny market cap)
- Cycle 2 (2011-2015): Weight = 1x
- Cycle 3 (2015-2018): Weight = 3x
- Cycle 4 (2018-2022): Weight = 5x
Formula: Weighted Avg = (C2×1 + C3×3 + C4×5) / (1+3+5)
Example for Bottom→Top days: (761×1 + 1065×3 + 1066×5) / 9 = 1,032 days
Projection Method
- Projected Top Date = Nov 2022 bottom + weighted avg Bottom→Top days
- Projected Bottom Date = Nov 2022 bottom + weighted avg Bottom→Bottom days
- Current days elapsed compared to weighted averages
- Warning symbol (⚠) shown when the current cycle exceeds the historical average
Technical Implementation
- Historical cycle dates are hardcoded (not algorithmically detected)
- Dates represent approximate monthly ranges for each event
- The indicator will be updated as the Cycle 5 top and bottom dates become confirmed
- Updates require manual code maintenance - not automatic
- Users should verify they're using the latest version for current cycle data
-----------------------------------------------------------------
FEATURES
- Background highlights for historical tops (red), bottoms (green), and halving events (yellow)
- Data table showing cycle durations and price changes
- Visual cycle boundary boxes with subtle coloring
- Projected timeframes displayed as dashed vertical lines
- Toggle on/off for each visual element
- Customizable background colors
-----------------------------------------------------------------
DISPLAY SETTINGS
- Show/hide cycle tops, bottoms, halvings, data table, and cycle boxes
- Customizable background colors for each event type
- Clean, institutional-grade visual design suitable for analysis
UPDATES & MAINTENANCE
This indicator is maintained as new cycle events occur. When Cycle 5's top and bottom are confirmed with sufficient time elapsed, the code and projections will be updated accordingly. Check for the latest version periodically.
OPEN SOURCE
Code available for review, modification, and improvement. Educational transparency is prioritized.
-----------------------------------------------------------------
IMPORTANT LIMITATIONS
⚠ EXTREMELY SMALL SAMPLE SIZE
Based on only 4 complete cycles (2011-2022). In statistical analysis, this is insufficient for reliable predictions.
⚠ CHANGED MARKET STRUCTURE
Bitcoin's market has fundamentally evolved since early cycles:
- 2010-2015: Tiny market cap, retail-only, unregulated
- 2024-2025: Institutional adoption, spot ETFs, regulatory frameworks, macro correlation
The environment that created past patterns no longer exists in the same form.
⚠ NO PREDICTIVE GUARANTEE
Historical patterns can and do break. Market cycles are not laws of physics. Past performance does not guarantee future results. The next cycle may not follow historical averages.
⚠ LENGTHENING CYCLE THEORY
Some analysts believe cycles are extending over time (diminishing returns, maturing market). If true, simple averaging underestimates future cycle lengths.
⚠ SELF-FULFILLING PROPHECY RISK
The halving narrative may be partially circular - it works because people believe it works. Sufficient changes in market structure or participant behavior can invalidate the pattern.
⚠ APPROXIMATE DATA
Historical prices rounded to significant figures. Exact bottom/top dates vary by exchange. Month-long ranges are used for simplicity.
EDUCATIONAL USE ONLY
This indicator is designed for historical analysis and understanding Bitcoin's past behavior. It is NOT:
- Trading advice or financial recommendations
- A guarantee or prediction of future price movements
- Suitable as a sole basis for investment decisions
- A replacement for fundamental or technical analysis
The projections show "what if the pattern continues exactly" - not "what will happen."
Always conduct independent research, understand the risks, and consult qualified financial advisors before making investment decisions. Only invest what you can afford to lose.
BTC Time CycleThis indicator helps track Bitcoin's historical four-year cycles by dividing time from market bottoms into Fibonacci-based segments, providing clear visual cues for potential bullish and bearish phases.
How It Works: This indicator overlays repeating Fibonacci-based time cycles onto weekly BTC charts , plotting vertical lines at key Fib ratios (0, 0.25, 0.382, 0.5, 0.618, 0.75, 1.0) to track cycle progress. Each cycle concludes at 1.0 and seamlessly resets as the next cycle's 0, capturing historical trough-to-trough intervals like those observed from 2018 to 2022. The week preceding the 0.75 Fibonacci ratio typically signals the cycle peak and bear market onset, transitioning through the final phase until 1.0 initiates a new cycle.
Disclaimer: This pattern has consistently repeated in past cycles, but financial markets are inherently unpredictable—it is not guaranteed to persist and remains valid only until disproven. Treat it as an analytical aid, not a predictive certainty.
This is merely a curiosity and is: True until it isn't™
Cycle Indicator CS7This indicator visualizes cyclical structures (including inverse cycles) for financial instruments.
It is highly customizable and comes with a default configuration optimized for cryptocurrencies on a 45-minute timeframe, highlighting the following cycles:
• T-3: Daily cycles
• T-2: Approximately 2-day cycles
• T+1: Bi-weekly cycles
• T-1: Approximately 4-day cycles
• T: Weekly cycles
The same setup can also be applied effectively on a 24-hour timeframe, highlighting the following longer-term cycles:
• T+2: Monthly cycles
• T+3: Quarterly cycles
• T+4: Semi-annual cycles
• T+5: Annual cycles
• T+6: Bi-annual cycles
Users can customize the configurations to suit the specific characteristics of any financial instrument.
Additionally, the indicator includes a prediction system that approximates future cycles, marking them with a “?”.
Trend Pro V2 [CRYPTIK1]Introduction: What is Trend Pro V2?
Welcome to Trend Pro V2! This analysis tool give you at-a-glance understanding of the market's direction. In a noisy market, the single most important factor is the dominant trend. Trend Pro V2 filters out this noise by focusing on one core principle: trading with the primary momentum.
Instead of cluttering your chart with confusing signals, this indicator provides a clean, visual representation of the trend, helping you make more confident and informed trading decisions.
The dashboard provides a simple, color-coded view of the trend across multiple timeframes.
The Core Concept: The Power of Confluence
The strength of any trading decision comes from confluence—when multiple factors align. Trend Pro V2 is built on this idea. It uses a long-term moving average (200-period EMA by default) to define the primary trend on your current chart and then pulls in data from three higher timeframes to confirm whether the broader market agrees.
When your current timeframe and the higher timeframes are all aligned, you have a state of "confluence," which represents a higher-probability environment for trend-following trades.
Key Features
1. The Dynamic Trend MA:
The main moving average on your chart acts as your primary guide. Its color dynamically changes to give you an instant read on the market.
Teal MA: The price is in a confirmed uptrend (trading above the MA).
Pink MA: The price is in a confirmed downtrend (trading below the MA).
The moving average changes color to instantly show you if the trend is bullish (teal) or bearish (pink).
2. The Multi-Timeframe (MTF) Trend Dashboard:
Located discreetly in the bottom-right corner, this dashboard is your window into the broader market sentiment. It shows you the trend status on three customizable higher timeframes.
Teal Box: The trend is UP on that timeframe.
Pink Box: The trend is DOWN on that timeframe.
Gray Box: The price is neutral or at the MA on that timeframe.
How to Use Trend Pro V2: A Simple Framework
Step 1: Identify the Primary Trend
Look at the color of the MA on your chart. This is your starting point. If it's teal, you should generally be looking for long opportunities. If it's pink, you should be looking for short opportunities.
Step 2: Check for Confluence
Glance at the MTF Trend Dashboard.
Strong Confluence (High-Probability): If your main chart shows an uptrend (Teal MA) and the dashboard shows all teal boxes, the market is in a strong, unified uptrend. This is a high-probability environment to be a buyer on dips.
Weak or No Confluence (Caution Zone): If your main chart shows an uptrend, but the dashboard shows pink or gray boxes, it signals disagreement among the timeframes. This is a sign of market indecision and a lower-probability environment. It's often best to wait for alignment.
Here, the daily trend is down, but the MTF dashboard shows the weekly trend is still up—a classic sign of weak confluence and a reason for caution.
Best Practices & Settings
Timeframe Synergy: For best results, use Trend Pro on a lower timeframe and set your dashboard to higher timeframes. For example, if you trade on the 1-hour chart, set your MTF dashboard to the 4-hour, 1-day, and 1-week.
Use as a Confirmation Tool: Trend Pro V2 is designed as a foundational layer for your analysis. First, confirm the trend, then use your preferred entry method (e.g., support/resistance, chart patterns) to time your trade.
This is a tool for the community, so feel free to explore the open-source code, adapt it, and build upon it. Happy trading!
For your consideration @TradingView
BTC Lead(v3.32)Summary
A 15-minute, BTC-focused lead/divergence indicator designed for simple execution: when a ▲/▼ appears, start scaling in with small clips; when a ■ (black square) prints, it means the indicator’s edge has weakened (not that the market trend is over). Real-time expected move label and alert templates included. Do not fade the signal—if you must try the opposite side, wait until a ■ appears.
How to read the signals
▲ Green → Long bias increased
▼ Pink → Short bias increased
■ Black → Edge weakened; consider taking profits/standing aside
Multiple level markers on the same bar (L2/L3/L4) = stronger setup
Live label (top of chart)
A single line shows the Expected Move (%) with arrow and color-coded background (↑ green / ↓ pink) for instant direction clarity.
Tip: Use Replay to watch label → ▲/▼ → ■ sequences on past data.
Confidence filter (important)
|Expected Move| < 1% → treat as noise / ignore
If considering the opposite direction, wait for a ■ first (edge reduced).
Scope
Internal calculations are fixed to 15-minute resolution.
Built for BTC 15m. It may display on other crypto symbols/timeframes, but performance is not guaranteed.
Alerts
Ready-made conditions: ENTRY LONG / ENTRY SHORT / EXIT LONG / EXIT SHORT. Add an alert on this indicator and choose the condition you want.
Risk note
For research/education only. Past behavior doesn’t guarantee future results. Predefine position sizing, stops, and profit-taking, and execute consistently.
